Neuronformatics and Emerging TechnologiesFebruary 19, 2007 Team 3 - Tensa Zangetsu Chiranjeev Bordoloi Koch Geevarghese Romerl Elizes Yonesy Nunez
Agenda • Introduction • Definitions • Background • Current Work and Experiments • Current Support • Links • References
Introduction • Understanding the human nervous system is one of the greatest challenges of 21st century science • The topic we will focus on is neuroinformatics • The goal for this presentation is a general overview of neuroinformatics • Brain informatics is a subset of neuroinformatics, but most of the literature in neuroinformatics focuses on the brain
Definitions Neuroscience • Field devoted to the scientific study of the nervous system • Disciplines include: structure, function, development, genetics, biochemistry, pharmacology, and pathology. • Focuses on the investigation of the brain and mind.
Definitions Neuroinformatics • intersection of neuroscience and information science. • many points of contact between the neuroscience-related life-sciences and the information sciences and related disciplines: • Life sciences: neuroscience, neurology, psychology, linguistics, biology, chemistry, physics, etc. • Information sciences: computer science, mathematics, statistics, physics, electrical engineering, robotics, etc. • Goals of neuroinformatics: • developing and applying computational methods to the study of brain and behavior • applying advanced IT methods to deal with the huge quantity and great complexity of neuroscientific data • exploiting our insights into the principles underlying brain function to develop new IT technologies.
Background Neuroscience • In Egyptian times, the heart, not the brain, was classified as the seat of intelligence. • Hippocrates was the first to indicate that the brain was the seat of intelligence. • Roman physician, Galen, further backed this by providing evidence that Roman gladiators lost their mental faculties when they sustained severe damage to their brains. • Further studies of the brain was stagnant until the invention of the microscope. The work at first focused on the individual neurons.
Background Neuroscience • Camillo Golgi in the 1890’s silver chromate salt to reveal intricate structures of single neurons • Santiago Ramon y Cajal used Golgi’s information to develop the neuron doctrine. The hypothesis is that the functional unit of the brain is the neuron. • Santiago Ramon y Cajal and Camillo Golgi received the Nobel Prize in 1906 for Physiology for their work on the structure of the nervous system
Background Neuroinformatics • Neuroinformatics is formally established by the National Institute of Mental Health in 1993 under the Human Brain Project. • In the Bioinformatics realm, the Institute for Genomic Research was established in 1992 in Rockville, Maryland. • The exponential growth of information technologies especially the Internet in the 1990’s has prompted the growth of neuroinformatics.
Background Neuroinformatics • By 2000, 40 web-based projects with digital databases were steered by the Human Brain Project • This work impacts molecular biology and cellular physiology • Society of Neuroscience is formally established in 2003 to prompt the development and popularization of neuroscience to the world community. • In 2004, Program in International Neuroinformatics was established by 16 countries and the EU commission to promote international collaboration, dialogue, and support mechanisms for neuroscience application research.
Current Work and Experiments • This section will focus on: • Posit Science • Brain-Gene Ontology Project • Human Brain Mapping • Brain Computer Interface • Snapshot of published papers in Neuroinformatics
Current Work and Experiments Posit Science • Dr. Michael Merzenich and Dr. Henry Mahncke with other scientists developed a hypothesis designed to rejuvenate the brain’s plasticity. • Posit Science Inc. was founded in 2003 in San Francisco to develop a software program that could test and validate these neuroscientists’ hypothesis.
Current Work and Experiments Posit Science • The connections in the brain are plastic, meaning that when we learn something, the properties of our synapses and other neural circuits change, thus improving their processing speed and the fidelity of the information encoded. • As we age, this natural learning process starts to deteriorate. This slowing is at the root of some age-related memory loss. • Recent research has shown that reading the newspaper or doing crosswords can help keep older people mentally fit.
Current Work and Experiments Posit Science • Dr. Merzenich research study involves the subjects being asked questions from recorded narratives. • The narratives are played slowly at first and progressively become faster. • The narratives are easy at first and progressively become difficult. • The narratives are delivered via a computer-based training module with minimal interaction with researchers. • The level of challenge is crucial component in triggering brain plasticity. • The study was conducted with 95 older people aged 63-94. • The exercises were: speed of processing, spatial syllable match memory, forward word recognition span, working memory, and narrative memory. • The goal was for the subjects to train one hour a day for eight weeks.
Current Work and Experiments Posit Science • Results • People who trained the full eight weeks significantly improved their scores on memory tests. • People who progressed to the most difficult levels of the narratives showed the greatest improvements. • Majority of participants gained ten neurocognitive years. • Exercise results: • Speed of Processing – 93% of participants improved by 41% • Spatial syllable match memory – 77% of participants improved by 10% • Forward word recognition span – 91% of participants improved by 18% • Working memory – 80% of participants improved by 13% • Narrative memory – 91% of participants improved by 18%
Current Work and Experiments Posit Science • Other disciplines affected: gerontology. • Papers derived from this work: • Brain plasticity and functional losses in the aged: scientific bases for a novel intervention • Memory enhancement in healthy older adults using a brain plasticity-based training program: A randomized, controlled study
Current Work and Experiments Brain-Gene Ontology • Nikola Kasabov, Vishal Jain, and other authors from Auckland University of Technology in New Zealand undertook the Brain-Gene Ontology (BGO) Project: mapping the relationship between the brain and the genes. • The goals of the BGO project, through a software application, are to find if these relationships can be used for further investigations in neuroinformatics and bioinformatics. • A side goal of the BGO project is that it can be used as a training tool for researchers and students. • The project was presented in the Sixth Annual Conference of Hybrid Intelligent Systems in December 2006 under the title: “Brain-Gene Ontology: Integrating Bioinformatics and Neuroinformatics Data, Information and Knowledge to Enable Discoveries.”
Current Work and Experiments Brain-Gene Ontology • BGO application consists of three parts: • Brain organization and function – contains information about neurons, synapses and electroencephalogram (EEG) data for normal and epileptic brain states. • Gene regulatory network – contains sections on neuro-genetic processing, gene expression regulation, protein synthesis, and abstract GRN. • Simulation modeling – contains sections on computational neurogenetic modeling (CNGM), evolutionary computation, evolving connectionist systems, spiking neural network, simulation tools, and CNGM results
Snapshot of the BGO detail showing relations between genes, proteins, neuronal functions and diseases
Current Work and Experiments Mitre Corporation – Human Brain Mapping • Human brain mapping data (MRI, fMRI, Cryosection, EEG, etc.) is rapidly accumulating worldwide (many terabytes) • but it is not widely shared • potential value of it’s scale is not being realized • Significant need for an appropriate information infrastructure. • Our goal: “The goal of this proposal is to enable the world-wide exploration, analysis, and dissemination of the growing corpus of human brain mapping information.” • Three basic architecture components: • digital library, associated repository, warehouse • Five basic workflows: • submission, retrieval, migration, definition, exploration
Overview Of Proposed System: 5 Processes 5 4 Warehouse Atlas Generation Exploration - brain attributes - visualization - spatial reasoning - content-based retrieval Features Probabilistic Atlases Volume= 3.2 3 Migration Digital Library Metadata Repository Retrieval Data Archive partitions 2 gender race test score .... Submission 1
Process 1: Submission To Library Metadata Repository Data Archive (structural MRI partition) non-core core images race gender age test scores genetic info scan conditions etc.... tissue-labeled, scalped, normalized noise (motion) corrected * reconstructed PD T1 T2 * (256 x 256 x 170 voxel matrix) Data Validation Tests Mapping Data survey test (1) test (2) etc. Associated Metadata
Process 2: Retrieval From Library Query Selected Data Apply Access Policy Data Archive (structural MRI partition) non-core core images Repository LRR* tissue-labeled, scalped, normalized race gender age test scores genetic info etc.... noise (motion) corrected * reconstructed PD T1 T2 * (Library Retrieval Request)
Process 3: Migration Into Warehouse Individual Brain Object*: Data Warehouse + + Feature Attributes Labeled Brain Volume Deformation Field Structural Brain Hierarchy * (One instance per core scanned brain) Extract Features And Annotate Structure Hierarchy Replicate Associated Metadata Voxel-Label Anatomic Regions Warp To A Standard Space, (Generate Deformation Field) core images T1 / tissue labeled brain volume Digital Library Repository
Process 4: Exploration Of Warehouse Describe Query Visualization Spatial Reasoning Content-based Retrieval Standard Attribute/Value “Extended” Feature Query Interface Data Warehouse Queries Answers Optimization Optional LRR Individual Brain Objects + + Feature Attributes Labeled Brain Volume Deformation Field Structural Brain Hierarchy
genotype Process 5: Atlas Definition Within Warehouse gender = male 25 < age < 30 Describe Subpopulation Characteristics “fact table” disease state etc (extensible) feature (e.g. hippocampal volume size) Atlas Definition Data Warehouse Composite Brain Objects: + + Feature Attributes Deformation Field Of Population Center To Standard Space Labeled Probabilistic Brain Volume Structural Brain Hierarchy
Process 4 (revisited): Exploration (Atlases) Describe Query Visualization Spatial Reasoning Population Comparison Standard Attribute/Value Query Interface Queries Answers Optimization Data Warehouse Atlas Data Model: + + Feature Attributes Deformation Field Of Population Center To Standard Space Labeled Probabilistic Brain Volume Structural Brain Hierarchy
Current Work and Experiment Brain Computer Interface • Nick Chisolm is a man who became paralyzed in a rugby accident at age 23 in 1998. • He suffers from locked-in syndrome which is a condition where you have lost almost all physical motion in the body but not the brain. The brain is still working at 100% efficiency. • Nick only had physical movement with his eyes. When he needed to compose a sentence or word, he had to use his eyes to indicate the validity of a letter of a word. • This rehabilitation process is time consuming and extremely frustrating for the victim. • His suffering prompted the work on BCI for paralyzed people.
Introduction • Brain-Computer Interface (BCI) is a device which allows the human to control electronic devices just by thinking. • Current BCIs are based on Electroencephalogram (EEG) . • Peirre Glorr and Hans Berger discovered EEG in 1969. • First BCI was built by Vidal in 1973 • For more than 2 decades no real development was done in BCIs, mostly waiting for the technology to catch up.
BCI- How does it Works? • Amplify the EEG signals. • Digitize the signals. • Elimination of unwanted signals • Other necessary manipulation. • Translate the signals to computer commands.
BCI- Goes Wireless • Wearable or Wireless BCI is developed because of the advanced communication devices. • Wireless BCI interact with a PDA equipped with is the best visualization. - Bluetooth – for portability • GPS -- to be aware of the environment • WLAN 802.11b– For access to the processing power in Office/Home.
BCI- Current Issues • BCI is interested only in EEG wavelets from the Cerebrum (Thinking Center) .Eliminating other wavelets like Electrooculogram (EOG) , Electromaygram (EMG), etc. is one issue. • Other Problems are: • Slow user response times • Excessive error rates • High cost • Actual appearance • Long initial training periods
Current Work and Experiments Brain Computer Interface • Paper from K. Navarro: “Wearable, Wireless Brain Computer Interfaces In Augmented Reality Environments” • Current BCI does not currently follow design principles of the Human Computer Interaction (HCI) discipline. BCI should use this knowledge and follow this “pattern language.” • Author proposes the use of Augmented Reality Environments (AR) for the BCI wearer. Augmented Reality systems enhance the real world by superimposing information onto it. Ex: pair of glasses with information overlaid on the screen. • Problem with making it reality: Developing a BCI for an AR environment addresses a specific problem. The goal of the BCI is to work in a highly changing environment.
Current Work and Experiments Brain Computer Interface • Dr. Jonathan Wolpow, Chief of Laboratory of Nervous Systems Disorders in NYS Department of Health: Wadsworth Center spearheads an extraordinary BCI initiative. • Dr. Scott Mackler is one of his success stories. Dr. Mackler suffers from progressive neurodegenerative disease. He lost all movement in 1999. • With the help of Wolpow’s innovative approaches to BCI implementation, Dr. Mackler still goes to work.
Current Work and Experiments Published papers from the Institute of Neuroinformatics for 2007: • Fast sensory motor control based on event-based neuromorphic-procedural systems • The role of first and second order stimulus features of human overt attention • Modulation of synchrony without changes in firing rates • Sleep-related spike bursts in HVC are driven by the nucleus interface of the nidopallium • Time and space are complementary in encoding dimensions in the moth antennal lobe. • Gamma range cortico-muscular coherence during dynamic force output • Implementing homeostatic plasticity in VLSI networks of spiking neurons
Current Support Human Brain Project • Sponsored by the National Institute of Mental Health of the National Institutes of Health • Established in 1993 to support the research efforts in neuroinformatics. • Find new ways in spearheading neuroinformatics research • Develop informatics tools and resources for neuroscience.
Current Support Human Brain Project - Agenda of Annual Meeting – April 24, 2006 • Current Initiatives: • Improving Image Analysis Tools • Create physiological data and exploit using simulation • Creation of ASTYNAX: A pilot exploration of web technology • Problems with Data gathering: • Data • Data heterogeneity • Lack of data standards • Cultural gap requires paradigm shift • Practice • Few repositories available for willing stakeholders • Information sparseness • Lack of Incentive
Current Support Insititute of Neuroinformatics • Established in 1995 by the University of Zurich • States that $1 trillion dollars is spent on neuroinformatics mosty on communications, processing, and information management. Creating autonomous intelligent systems is slow. • Projects pursued within the institute are: • Behavior and Learning in Intelligent Autonomous Systems • Representation and Sensory Motor Integration • Neuronal Architectures and Computation • Neuromorphic Chips and Systems • Neurotechnologies
Current Support Computational Neuroscience/Neuroinformatics • Aims to unravel the complex structure-function relationships of the brain at all levels from molecular to behavioral in an integrative effort with many scientific disciplines. • Based in Europe, the organization is one of the primary sponsors in conferences geared toward computational informatics. Some of these conferences are in United States and Canada as well. • Sixteenth Annual Computational Neuroscience Meeting CNS, Toronto, Canada – July 2007 • MBX – Special Topic Courses – Neuroinformatics, Wood Holes, MA – August 2006 • Tenth Annual Conference on Cognitive and Neural Systems, Boston MA – May 2006
Current Support NYS Department of Health: Wadsworth Center • Under Dr. Jonathan Wolpow’s supervision, are working on bring the BCI technology into home use. • Streamlined version of the Wadsworth BCI consists of: • laptop computer • portable amplifier • breathable cap which contains just 8 electrodes, down from the original 64 • currently about $4,000, but will price will drop as technology improves • Dr. Wolpow estimates that 70-80% with severe disabilities could use the Wadsworth BCI System. • Heavy funding from NIH for the next few years.
Links • “Brain-Computer Interfaces Come Home.” National Institutes of Health: National Institute of Biomedical Imaging and Bioengineering. November 28, 2006. http://www.nibib.nih.gov/HealthEdu/PubsFeatures/eAdvances/28Nov06 • “The Brain Computer Interface with Natasha Mitchell.” AllInTheMind, ABC National Radio, Austraila. December 2, 2006. http://abc.net.au/rn/allinthemind/stories/2006/1799619.htm • Computational Neuroscience/Neuroinformatics. http://www.hirnforschung.net/cneuro/ • The Human Brain Project. National Institutes of Health: National Institute of Mental Health. http://www.nimh.nih.gov/neuroinformatics/ • Institute of Neuroinformatics. University of Zurich. http://www.ini.unizh.ch/public/ • Mitre Corporation : Neuroinformatics website. http://neuroinformatics.mitre.org/index.html • Neuroinformatics. Wiki site. http://en.wikipedia.org/wiki/Neuroinformatics • Neuroscience. Wiki site. http://en.wikipedia.org/wiki/Neuroscience • Wadsworth Center: New York State Department of Health. Home page. http://www.wadsworth.org/index.html
References • N. Kasabov, V. Jain, P. Gottgtroy, L. Benuskova, F. Joseph. “Brain-Gene Ontology: Integrating Bioinformatics and Neuroinformatics Data, Information and Knowledge to Enable Discoveries.” Proceedings of the Sixth International Conference on Hybrid Intelligent Systems (HIS'06), pp. 13. December 2006. • H. Mahnke, A Bronstone, MM Merzenich. “Brain plasticity and functional losses in the aged: scientific bases for a novel intervention.” Journal of Progress in Brain Research. Volume 157. p. 81-109. 2006 • H. Mahnke, B. Connor, J. Appelman, O. Ahsanuddin, J. Hardy, R. Wood, N. Joyce, T. Boniske, S. Atkins, M. Merzenich. “Memory enhancement in healthy older adults using a brain plasticity-based training program: A randomized, controlled study.” Procceedings of the National Academy of Sciences. August 23, 2006. • K. Navarro. “Wearable, wireless brain computer interfaces in augmented reality environments.” Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2, p. 643. April 2004 • E. Singer. “Exercising the Brain: Innovative training software could turn back the clock on aging brains.” Technology Review, Massachusetts Institute of Technology, Cambridge, MA. November 21, 2005 • Wearable, Wireless Brain Computer Interfaces In Augmented Reality Environments. By Karla Felix Navarro, University of Technology, Sydney IEEE 2004 • P300 Detection for Brain-Computer Interface from Electroencephalogram Contaminated by Electrooculogram. By Motoki Sakai, Hiroyuki Ishita, Yuuki Ohshiba, Wenxi Chen, and Daining Wei Graduate School of Computer Science and Engineering, The University of Aizu, Ikki-machi, Aizu- Wakamatsu City, Fukushima 965-8580, Japan IEEE 2006